code: def test_broadcast_all(shapes):
      inputs, dim_to_symbol, symbol_to_dim = make_inputs(shapes)
      packed_inputs = [packed.pack(x, dim_to_symbol) for x in inputs]
      packed_outputs = packed.broadcast_all(*packed_inputs)
      actual = tuple(
          packed.unpack(x, symbol_to_dim) for x in packed_outputs
      )
      expected = broadcast_all(*inputs) if inputs else []
      assert len(actual) == len(expected)
      for a, e in zip(actual, expected):
          assert_equal(a, e)
  
file_path: pyro/tests/ops/test_packed.py
imports: import itertools
  import random
  import pytest
  import torch
  from torch.distributions.utils import broadcast_all
  from pyro.ops import packed
  from tests.common import assert_equal
label_desc: Use image node_id 3 for calling a global function with example usage: test_broadcast_all(shapes) without return types